AI Reader X

\[file name\]: Turning books into knowledge graphs, distilling them into skills, enabling intelligent dialogue with books, with 13 built-in AI conversation modes. In the AI era, transforming book knowledge into a living knowledge base that becomes your 24/7 deep-learning private tutor — you can both ask the tutor questions and let the tutor ask you questions, greatly improving learning efficiency. You can also turn conversation results into notes with one click, making knowledge permanent. Includes 180 distilled skill packs from famous figures across ages and cultures, supporting one-on-one dialogue or multi-person group chats.

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13 Conversation Modes:

1. Standard Conversation: A general-purpose mode that answers questions based on the full book content and the knowledge graph. It loads chapter summaries and graph overviews, provides accurate answers with specific chapter citations, uses clear language and Markdown formatting; when a question goes beyond the book's scope, it honestly states so. This is the most commonly used entry mode, suitable for daily reference and free Q&A.

Example: Select "Standard Conversation" and ask — "What are the main reasons for the decline of the Jia family? Please cite relevant chapters."

2. Instant Learning Guide: Acts as a learning mentor, generating instant learning guidance around your question. It cites core concepts and cross‑chapter connections from the book, helping you build a knowledge system. Each answer comes with specific knowledge point citations, avoiding vague generalities. Suitable for systematic study of a book, structuring your understanding, and filling gaps.

Example: Select "Instant Learning Guide" and ask — "I want to systematically understand the first twenty chapters. Help me sort out the key characters, main plotlines, and learning sequence."

3. Socratic Questioning: Uses Socratic follow‑up questions based on the full book content to guide deep thinking through consecutive questions. It does not give direct answers; instead, it poses one question at a time and adjusts the direction based on your responses, citing chapters to help you make connections. Suitable for actively testing your understanding and training critical thinking.

Example: Select "Socratic Questioning" and enter — "Let's discuss 'the Golden Match versus the Wood‑and‑Stone Bond'." Then answer the AI's follow‑up questions one by one.

4. Exam Predictor: Acts as an exam prediction expert, forecasting possible test questions based on the book content and core concepts in the graph. It provides question types (multiple‑choice, short‑answer, essay) with sample answer outlines, focusing on cross‑chapter synthesis questions, and cites specific chapters to support predictions. Suitable for pre‑exam cramming and review planning.

Example: Select "Exam Predictor" and ask — "For the section 'Daiyu Buries Flowers', predict possible essay questions and give answer outlines."

5. Confusion Terminator: Focuses on resolving your doubts, explaining concepts in simple language with citations from the book. It lists related concepts, provides examples and analogies, points out easily confusable similar concepts, and gives suggestions for further study. Suitable when you're stuck on a difficult point and need to quickly clarify a concept.

Example: Select "Confusion Terminator" and ask — "I always mix up 'Golden Match' and 'Wood‑and‑Stone Bond'. Please help me distinguish the two."

6. Mock Exam: Acts as a mock exam system, generating a complete test paper (at least five questions) covering various question types based on the full book. Questions span core concepts across chapters and include cross‑chapter synthesis items. Each question comes with a standard answer, scoring criteria, and chapter references. Suitable for full self‑assessment and checking overall mastery.

Example: Select "Mock Exam" and enter — "Please generate a mock exam paper based on the entire book, including multiple‑choice, short‑answer, and essay questions."

7. Teaching Feedback Test: Inspired by the Feynman Technique, it lets you explain a concept in your own words, then compares your explanation against the original text to evaluate accuracy and completeness. It points out missing points, cites specific chapters, and gives encouraging suggestions for improvement. Suitable for deep internalisation through "learning by teaching".

Example: Select "Teaching Feedback Test" and enter — "Here's my explanation of the role of 'the Land of Illusion': … Please assess whether my understanding is accurate and whether anything is missing."

8. /query Knowledge Q&A: A command for Q&A based on the knowledge graph. It combines graph query results with original text, explains the queried nodes and relationships in natural language; if fuzzy matching occurs, it informs you of the actual matched nodes; if results are empty, it suggests related concepts and keywords. Suitable for exploring concepts from a graph perspective.

Example: Enter /query Jia Baoyu — queries the node and its neighbouring relations and provides an interpretation.

9. /explain Node Explanation: Focuses on a single concept, explaining its position and importance in the knowledge graph. It lists outgoing edges (influences) and incoming edges (influenced by), analyses the concept's role in the overall knowledge system, and cites chapter text for support. Suitable for gaining a comprehensive understanding of a core concept.

Example: Enter /explain Grand View Garden — explains the node's graph position, incoming/outgoing edge relations, and systemic role.

10. /neighbors Neighbour Details: Displays all neighbour relationships of a concept. It lists outgoing edges (concepts it points to) and incoming edges (concepts pointing to it), grouped by relation type, analyses the concept's hub‑degree in the network, and cites chapter content. Suitable for understanding the direct association network of a concept.

Example: Enter /neighbors Lin Daiyu — lists all characters and concepts directly connected to this character.

11. /path Path Analysis: Analyses the connection path between two concepts. It explains the role and significance of each intermediate concept on the path, dissects the academic meaning of the path; if no direct path exists, it suggests possible intermediary concepts; in case of fuzzy matching, it informs you of the actual start/end nodes. Suitable for understanding how two concepts are linked.

Example: Enter /path Jia Baoyu → Wang Xifeng — analyses the connection path and intermediate nodes between the two (separate with → or a space).

12. /compare Concept Comparison: Compares the definitions and characteristics of two concepts. It analyses shared neighbours and unique associations of each, highlights similarities and differences, explains any direct relationship between them, and presents the comparison in a table or list, finally summarising their differing positions in the overall knowledge system. Suitable for distinguishing similar concepts.

Example: Enter /compare Lin Daiyu and Xue Baochai — compares the two concepts (separate with "and" or a comma).

13. /summary Graph Overview: Generates an overall analysis report of the full‑book knowledge graph. It summarises graph scale and structural features, analyses node type distribution, lists the highest‑degree core nodes and the tightest concept pairs, and gives overall evaluation and exploration suggestions based on the book content. Suitable for a bird's‑eye view of the entire knowledge structure.

Example: Enter /summary — no parameters; directly generates the full‑graph overview report.